System and method for optimized mobility management in a wireless network

ABSTRACT

A mobility management optimizing function in a wireless network receives geographic location information associated with a user equipment device (UE), wherein the UE is associated with a vehicle and generates a predictive handover schedule based on the received location information. Handover processing is initiated based on the predictive handover schedule, wherein initiating the handover processing comprises: transmitting one or more handover initiation messages to a plurality of cell sites in a service provider wireless network at times based on the predictive handover schedule, wherein, upon receipt of a handover initiation message, the plurality of cell sites will initiate handover processing based on the received handover initiation message.

BACKGROUND

Next Generation mobile networks, such as Fifth Generation (5G) mobilenetworks, are expected to operate in the higher frequency ranges, andsuch networks are expected to transmit and receive in the gigahertz(GHz) band with a broad bandwidth near 500-1,000 megahertz (MHz). Theexpected bandwidth of Next Generation mobile networks is intended tosupport download speeds of up to about 20 gigabits per second. Theproposed 5G mobile telecommunications standard, among other features,operates in the millimeter wave bands (e.g., 14 (GHz) or higher), andsupports more reliable, massive machine communications (e.g.,machine-to-machine (M2M), Internet of Things (IoT), etc.). NextGeneration mobile networks, such as those implementing the 5G mobiletelecommunications standard, are expected to enable a higher utilizationcapacity than current wireless systems, permitting a greater density ofwireless users, with a lower latency. Next Generation mobile networks,thus, are designed to increase data transfer rates, increase spectralefficiency, improve coverage, improve capacity, and reduce latency.

Millimeter wave (mmWave) frequencies are proposed to be used in advancedwireless systems, such as, for example, 5G systems. mmWave frequenciesare limited in coverage, but are able to penetrate buildings more thanlower frequency waves. Due to these limitations, cell sites containingthe system antennas need to be close to the network user to make up forthe signal losses. This requires a greater cell density in the advancedwireless systems, relative to current systems. Additionally, to satisfythe improved utilization capacity requirements of advanced wirelesssystems, a greatly increased number of antennas, relative to currentsystems (e.g., Fourth Generation (4G) systems), will need to be deployedto support high bandwidth connections to each wireless device. Incurrent wireless systems, the typical distance between adjacent antennasis about 1.5-3.2 kilometers (km). In contrast, for proposed advancedwireless systems, such as 5G systems, the distance between adjacentantennas may need to be reduced to about 200-300 meters. Therefore, nextgeneration wireless systems may need as many as one hundred times thenumber of antennas as compared to current wireless systems.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an overview of a system consistent with embodimentsdescribed herein;

FIG. 2 illustrates overview of an exemplary network environment in whichsystems and methods described herein may be implemented;

FIG. 3 depicts an example of intra- and inter-cell site handoverconsistent with implementations described herein;

FIG. 4 is a block diagram illustrating example components of a computerdevice 400 according to one embodiment;

FIG. 5 is a block diagram illustrating exemplary functional componentsof and information stored in the mobility management optimizationfunction of FIG. 2, according to embodiments described herein;

FIG. 6 is a flow diagram of an exemplary process for optimizing mobilitymanagement consistent with embodiments described herein;

FIG. 7 is a signal diagram illustrating exemplary processing ofschedule-based beam switching consistent with embodiments describedherein; and

FIG. 8 is a signal diagram illustrating exemplary processing of theschedule-based inter-cell site handover consistent with embodimentsdescribed herein.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following detailed description refers to the accompanying drawings.The same reference numbers in different drawings may identify the sameor similar elements. The following detailed description does not limitthe invention, which is defined by the claims.

Fifth Generation (5G) radio deployments at mmWave frequencies requiremore line of sight antenna installations as compared to current FourthGeneration (4G) radio deployments. Additionally, 5G cell deploymentswill be much denser than current 4G cell deployments, and mmWave 5Gantennas will be much smaller and more directional than 3G or 4Gantennas. Furthermore, 5G antennas are expected to be deployed on poles,lamp posts, bus stops, and other more open locations, that are moresusceptible to environmental and human factors that may negativelyaffect the deployment environment of the antennas.

One of the promising applications to make use of such 5G mmWavefrequencies revolves around V2X (Vehicle-to-Everything) technology inwhich 5G systems provide the platform for the smart vehicles to beconnected to the network, taking advantage of the access to the networkfor in-car entertainment as well as providing necessary connectivity tosupport the vehicle safety, navigation, and diagnostic needs. In-carentertainment applications expect to be supported by as much as 4gigabits per second (Gb/s) instant data rate. A 5G mobile network canaccomplish such a rate via broadband spectrum solutions, such as mmWavespectrum (e.g., 24 GHz, 29 GHz, 38 GHz, etc.).

However, because the propagation characteristics of mmWave are such thatthe usable coverage of mmWave cell rarely exceeds 500 m (subject toshadowing impact of vehicles and terrain/clutter limitations) andvehicular speeds alongside the highways can exceed 80 miles per hour(approx. 36 m/s), frequent mobility management processing becomesnecessary (e.g., intra-cell and inter-cell handovers), consequentlyleading to increased 5G control channel load and demands on systemprocessing capacity.

Traditional wireless network mobility management mechanisms are based onuser equipment device measurements (e.g., relative downlink signalstrength) and clear delineation (e.g., using hysteresis) between theserving and adjacent cells' signal strengths and/or quality levels.However, this process takes relatively long time and uses many controlchannel resources to accomplish. Consequently, a deleterious number ofhandover failures, radio link failures, or complete device disconnectsmay occur, leading to a dramatic degradation of user perceivedperformance.

In addition, for 5G cell sites, 5G mmWave cell solutions supportbeamforming, in which the coverage area of the cell is internallydivided into a number of areas (e.g., 8, 16, 32, etc.) for separateantenna beams to improve the coverage and peak rate for users, as wellas reduce overall system interference. A user equipment device in aconnected mode is typically served within one beam at any point of timeand, as it moves (e.g., alongside the highway), the device is expectedto switch the beams. By way of example, assuming a cell site provideseight discrete antenna beams in its coverage area alongside a highway,the user equipment device may change the beam to which it connects asmuch as eight times within the cell site. Further assuming that the cellsite has a coverage range of 500 meters and the user equipment device istraveling at 36 meters per second, it may be necessary to change beamswithin the cell site coverage area approximately every 1.75 seconds.

Because of the speed of the device and the number of necessary beams atcell sites, the device may not trigger the required measurements on timeto initiate successful, uninterrupted intra- and inter-cell sitehandovers when the serving cell site or beam coverage is still reliable,thus degrading the performance or losing the radio link. The latter maylead to a radio link failure (RLF). Further, the moving device maytrigger frequent control channel activity to support beam switching andmobility handovers that contribute to the device's overheating issues,possibly leading to the device shutdown. In addition, 5G mmWave mobilenetwork may become overloaded with control messages that consumevaluable network resources.

Exemplary embodiments described herein implement an optimized mobilitymanagement mechanism when the network determines that a device isentering a predictable, high speed environment, such as a high-speedroadway or rail line. In particular, a predictive handover schedule maybe generated and implemented at a 5G node based on, for example, thelocation, speed, and direction of travel of the user equipment device.Based on the handover schedule, mobility processing may be performed totransition the user equipment device between cell sites withoutrequiring user equipment-based measurement control signaling, ordecision making.

Although embodiments described herein relate generally to in-vehicleuser equipment devices, the methods and systems described may besimilarly applied to any user equipment devices that travel a known orpredictable path of travel. For example, navigation to a predefinedlocation, historical travel patterns, etc.

FIG. 1 illustrates an overview of a system 100 consistent withembodiments described herein. As shown, system 100 includes a roadway105, cellular site devices 110-1 to 110-x (referred to collectively ascell sites 110) positioned proximate to roadway 105, a user equipment(UE) device 115 associated with a vehicle traveling on roadway 105, anda service provider network 120 operatively coupled to the cell sites110.

Consistent with embodiments shown herein, service provider network 120includes a mobility management optimization function 122 configured todetermine when UE device 115 has entered roadway 105 and optimizeintra-cell site and inter-cell site handover processing based on such adetermination. For example, service provider network 120 may retrieve orotherwise calculate vehicle information including at least location andother telemetry information associated with UE device 115, such asacceleration and velocity information, direction of travel information,etc. When it is determined that UE device 115 is entering roadway 105based on the retrieved or calculated vehicle information, mobilitymanagement optimization function 122 may determine a direction and rateof travel of UE device 115 as well as additional environmentalinformation, such as historical road traffic patterns, etc., and maypredict handover requirements for UE device 115. Mobility managementoptimization function may execute the predicted handovers as UE device115 travels on roadway 105, for optimal device-to-network communication.

As identified above, in traditional mobility management processing,certain signals may be exchanged between UE device 115 and cell sites110 prior to a handover. For example, prior to a traditional inter-cellsite handover, beam reference signals (BRS) or other reference signalsmay be received by UE device 115 from each of a source cell site 110 anda target cell site 110. In response, the UE device may generate ameasurement report (MR) and transmit the MR to the source cell site 110,which then, based on the content of the MR, initiates the handover tothe target cell site 110. Unfortunately, as identified above, in some 5GmmWave implementations involving high speed UE devices, such an overheadin handover processing and signaling may have deleterious effects onnetwork performance.

Accordingly, consistent with embodiments described herein, mobilitymanagement optimization function 122 may predict and initiate executionof handovers while the UE device 115 remains on roadway 105, thusremoving the overhead signaling and processing required in traditionalhandovers.

FIG. 2 illustrates overview of an exemplary network environment 200 inwhich systems and methods described herein may be implemented. As shown,network environment 200 includes base stations 205-1 through 205-x,antenna arrays 210, UE devices 215-1 through 215-y, a mobilitymanagement optimization function 230, and one or more networks 240.

Base stations 205-1 through 205-x (referred to herein as “base station205” or “base stations 205”) may each include a base station of a PublicLand Mobile Network (PLMN), or other type of wireless station. Each ofbase stations 205 may include one or more antenna arrays 210 and controlthe transmission and reception of data via a wireless interface. Each ofbase stations 205 may include, for example, a Node B, an Evolved Node B(eNB), or a Next Generation Node B (gNB) of a PLMN (e.g., ThirdGeneration (3G), Fourth Generation (4G), or Fifth Generation (5G) PLMN).

Each base station 205 may, in some implementations, be split intovarious components and located in a distributed fashion. For example,base station 205 may be split into a base band unit (BBU) and multipleremote radio heads (RRHs), where the BBU may be located at a differentlocation than the RRHs and may connect to the RRHs via, for example,optical fibers. Each BBU includes a network device that operates as thedigital function unit that transmits digital baseband signals to theRRHs and receives digital baseband signals from the RRHs. If the BBU isconnected to the RRHs via, for example, optical fibers, then the BBU mayconvert the digital baseband signals into corresponding optical signalsfor transmission to the RRHs. The BBU may also receive optical signalsfrom the RRHs and convert the optical signals into corresponding digitalbaseband signals. The RRHs include network devices that operate as radiofunction units that transmit and receive radio frequency (RF) signalsto/from UE devices (e.g., UE device 115). If the RRHs are connected tothe BBU via an optical fiber, the RRHs may convert received RF signalsto optical signals and transmit the optical signals to the BBU.Additionally, the RRHs may receive optical signals from the BBU via theoptic fiber, convert the optical signals to RF signals for transmissionvia one or more antenna arrays of the RRHs. Each of the RRHs may includeat least one antenna array, a transceiver, and other hardware andsoftware components for enabling the RRHs to receive data via wirelessRF signals from UE devices 115, and to transmit wireless RF signals toUE devices 215.

Antenna arrays 210 (referred to herein as “antenna array 210” or“antenna arrays 210”) may each include an array of antennas, such as,for example, a FD-MIMO or massive MIMO antenna array, that may formantenna beams in horizontal and/or vertical directions to enable eacharray of antennas to cover a three-dimensional space in the vicinity ofeach array 210. For example, each antenna array 210 may include a numberof horizontal antennas and a number of vertical antennas arranged in arows-and-columns configuration. As an example, an antenna array 210 mayinclude a 2×4 array with the 2 rows×4 columns of antennas. The antennaarrays 210 shown in FIG. 1 may service a wireless network coverage area220 within which UEs 215 may transmit to, and receive from, antennaarrays 110 via wireless transmissions. Antenna array 210 may providereliable wireless connections over area 220 and provide support for amaximum capacity and throughput.

A “cell site,” as referred to herein, includes a base station 205, andthe antenna arrays 210 to which base station 205 connects and that areused by the base station 205 for transmitting data to UEs 215, and forreceiving data from UEs 215. As shown in FIG. 2, base station 205-1 andconnected antenna arrays 210 represent cell site 225-1, base station205-2 and connected antenna arrays 210 represent cell site 225-2, andbase station 205-x and connected antenna arrays 210 represent cell site225-x. Each cell site 225 provides wireless network coverage in aparticular geographic area based on the antenna beams of the antennas ofeach antenna array 210. In particular, as briefly described above, cellsites 225 may correspond to a particular high speed roadway, such as alimited access interstate highway, in which vehicles carrying orembodying UE devices 215 may be traveling. Each antenna of the antennaarrays 210 may form a single beam of radio coverage. In someimplementations, each antenna may use a series of antenna elements toform the single beam of radio coverage. As described above, in someimplementations, each base station 105 may include multiple distributedcomponents (e.g., a BBU and multiple RRHs).

UE devices 215-1 through 215-y (also referred to herein as “UE 215” or“UEs 215”) each includes any type of device having one or more wirelesscommunication interfaces for communicating via antenna arrays 210, basestations 205, and network 240. The UEs 215 may each include, forexample, a cellular radiotelephone; a smart phone; a personal digitalassistant (PDA); a wearable computer; a Machine-to-Machine (M2M) device;an Internet of Things (IoT) device; a Vehicle-to-Everything (V2X)device, a desktop, laptop, palmtop or tablet computer; or a mediaplayer. Each UE 215 may connect to network 240 via a wirelessconnection. A “user” (not shown in FIG. 2) may be associated with eachUE 215, and may be an owner, operator, and/or a permanent or temporaryuser of the UE 215. Consistent with embodiments described herein, UE 215may be a mobile communication device capable of operation as part of ortraveling in a vehicle traveling at high speeds (e.g., overapproximately 50 miles per hour).

Mobility management optimization function 230 may include one or morenetwork devices that performs intelligent processes for optimizinghandover processing for UEs 215 and base stations 205. Mobilitymanagement optimization function 230 may, for example, perform theprocesses described below with respect to FIGS. 5-8 to optimize handoverprocessing. Consistent with embodiments described herein, mobilitymanagement optimization function 230 may be associated with orincorporated within an access and mobility function (AMF) associatedwith the portion of the networks 240 connected to cell sites 225.

Networks 240 may include one or more networks of various types, with atleast one network including a wireless network, such as, for example, aPLMN or a satellite mobile network. The PLMN may include a Code DivisionMultiple Access (CDMA) 2000 PLMN, a Global System for MobileCommunications (GSM) PLMN, a Long Term Evolution (LTE) PLMN, and/orother types of PLMNs. In addition to at least one wireless network,network(s) 140 may further include other types of telecommunicationsnetwork (e.g., Public Switched Telephone Networks (PSTNs)), a wiredand/or wireless local area network (LAN), a wired and/or wireless widearea network (WAN), a metropolitan area network (MAN), an intranet, theInternet, and/or a cable network (e.g., an optical cable network).

The configuration of the components of network environment 200 depictedin FIG. 2 is for illustrative purposes only, and other configurationsmay be implemented. Therefore, network environment 100 may includeadditional, fewer and/or different components, that may be configureddifferently, than depicted in FIG. 2.

FIG. 3 depicts an example of intra- and inter-cell site handoverconsistent with implementations described herein. As shown, FIG. 3illustrates a portion of roadway 105 serviced by a first cell site 225-1and a second cell site 225-2, each of which are connected to mobilitymanagement optimization function 230 via network(s) 240. Furthermore,FIG. 3 graphically depicts cell site service areas 300-1 and 300-2associated with each of first cell site 225-1 and second cell site225-2, respectively (depicted as solid ovals) and beam service areas305-1 to 305-16 associated with antenna beams provided by cell sites 225(depicted as dashed ovals). In the example of FIG. 3, each cell site 225outputs eight antenna beams that cover a portion of roadway 105. Asshown, in this example, cell site service areas 300-1 and 300-2 overlapto allow for effective inter-cell site handover from cell site 225-1 to225-2 without radio link failures. Similarly, each beam service area 305also overlaps with adjacent beam service areas 305 to allow forintra-cell site handover (i.e., beam switching) within the respectivecell site 225. This depiction is simple for descriptive purposes. In anactual environment, the number of antenna beams that service aparticular portion of a roadway may be more or fewer and may also havedifferent coverage areas, based on geography, topography, interveningstructures, cell site capabilities, etc.

UE device 215-1 (depicted as a vehicle in FIG. 3) is shown as travelingalong roadway 105 in a direction from first cell site 225-1 towardsecond cell site 225-2. Consistent with implementations describedherein, mobility management optimization function 230 periodicallymonitors the location, speed, and direction of travel of UE device215-1. Mobility management optimization function 230 determines whetherUE device 215-1 is on roadway 105 by, for example, mapping the reportedlocation of UE device 225-1 to known coverage areas of cell sites 225.Based on this determination and UE device's 225-1 speed and direction oftravel, mobility management optimization function 230 determines whetherto apply predictive mobility management consistent with embodimentsdescribed herein. For example, if it is determined that the speed of UEdevice 225-1 exceeds a predetermined threshold or that networkutilization and/or congestion exceeds a threshold, predictive mobilitymanagement is performed to improve performance and reliability.

As described herein, when mobility management optimization function 230determines to apply predictive mobility management, a handover schedulefor UE device 215-1 is generated. To generate the handover schedule,mobility management optimization function 230 determines a schedule fortiming both intra- (beam switching) and inter-cell site handovers basedon at least the speed and direction of travel of UE 225-1 as well ascurrent and historical traffic information for roadway 105, such astraffic congestion information, other active users speeds, etc. Once thehandover schedule is determined, mobility management optimizationfunction 230 notifies or instructs UE 215-1 to switch beams and or cellsites in accordance with the determined schedule. As described inadditional detail below in relation to FIGS. 6-8, handovers executed viaa predicted schedule eliminate signaling required by traditionalhandover mechanisms, thereby improving the speed and reliability of thenetwork.

FIG. 4 is a block diagram illustrating example components of a computerdevice 400 according to one embodiment. UE 215, cell-site 225, andmobility management optimization function 230 may each include one ormore computer devices 400. As shown in FIG. 4, computer device 400 mayinclude a bus 410, a processor 420, a memory 430, an input device 440,an output device 450, and a communication interface 460.

Bus 410 includes a path that permits communication among the componentsof computer device 400. Processor 420 may include any type ofsingle-core processor, multi-core processor, microprocessor, latch-basedprocessor, and/or processing logic (or families of processors,microprocessors, and/or processing logics) that executes instructions.In other embodiments, processor 420 may include an application-specificintegrated circuit (ASIC), a field-programmable gate array (FPGA),and/or another type of integrated circuit or processing logic.

Memory 430 may include any type of dynamic storage device that may storeinformation and/or instructions, for execution by processor 420, and/orany type of non-volatile storage device that may store information foruse by processor 420. For example, memory 430 may include a randomaccess memory (RAM) or another type of dynamic storage device, aread-only memory (ROM) device or another type of static storage device,a content addressable memory (CAM), a magnetic and/or optical recordingmemory device and its corresponding drive (e.g., a hard disk drive,optical drive, etc.), and/or a removable form of memory, such as a flashmemory.

Input device 440 may allow an operator to input information into device400. Input device 440 may include, for example, a keyboard, a mouse, apen, a microphone, a remote control, an audio capture device, an imageand/or video capture device, a touch-screen display, and/or another typeof input device. In some embodiments, device 400 may be managed remotelyand may not include input device 440. In other words, device 400 may be“headless” and may not include a keyboard, for example.

Output device 450 may output information to an operator of device 400.Output device 450 may include a display, a printer, a speaker, and/oranother type of output device. For example, output device 450 mayinclude a display, which may include a liquid-crystal display (LCD) fordisplaying content to the customer. In some embodiments, device 400 maybe managed remotely and may not include output device 450. In otherwords, device 400 may be “headless” and may not include a display, forexample.

Communication interface 460 may include a transceiver that enablesdevice 400 to communicate with other devices and/or systems via wirelesscommunications (e.g., radio frequency, infrared, and/or visual optics,etc.), wired communications (e.g., conductive wire, twisted pair cable,coaxial cable, transmission line, fiber optic cable, and/or waveguide,etc.), or a combination of wireless and wired communications.Communication interface 460 may include a transmitter that convertsbaseband signals to radio frequency (RF) signals and/or a receiver thatconverts RF signals to baseband signals. Communication interface 460 maybe coupled to one or more antennas/antenna arrays for transmitting andreceiving RF signals.

Communication interface 460 may include a logical component thatincludes input and/or output ports, input and/or output systems, and/orother input and output components that facilitate the transmission ofdata to other devices. For example, communication interface 460 mayinclude a network interface card (e.g., Ethernet card) for wiredcommunications and/or a wireless network interface (e.g., a WiFi) cardfor wireless communications. Communication interface 460 may alsoinclude a universal serial bus (USB) port for communications over acable, a Bluetooth wireless interface, a radio-frequency identification(RFID) interface, a near-field communications (NFC) wireless interface,and/or any other type of interface that converts data from one form toanother form.

Device 400 may perform certain operations relating to optimizing UEhandover processing in a wireless network. Device 400 may perform theseoperations in response to processor 420 executing software instructionscontained in a computer-readable medium, such as memory 430. Acomputer-readable medium may be defined as a non-transitory memorydevice. A memory device may be implemented within a single physicalmemory device or spread across multiple physical memory devices. Thesoftware instructions may be read into memory 430 from anothercomputer-readable medium or from another device. The softwareinstructions contained in memory 430 may cause processor 420 to performprocesses described herein. Alternatively, hardwired circuitry may beused in place of, or in combination with, software instructions toimplement processes described herein. Thus, implementations describedherein are not limited to any specific combination of hardware circuitryand software.

Although FIG. 4 shows exemplary components of device 400, in otherimplementations, device 400 may include fewer components, differentcomponents, additional components, or differently arranged componentsthan depicted in FIG. 4. Further, in some embodiments, one or more ofthe components described above may be implemented as virtual components,such as virtual processors, virtual memory, virtual interfaces, etc.Additionally, or alternatively, one or more components of device 400 mayperform one or more tasks described as being performed by one or moreother components of device 400.

FIG. 5 is a block diagram illustrating exemplary functional componentsof and information stored in mobility management optimization function230 according to embodiments described herein. The components ofmobility management optimization function 230 may be implemented, forexample, via processor 420 executing instructions from memory 430.Alternatively, some or all of the functional components of mobilitymanagement optimization function 230 may be implemented via hard-wiredcircuitry. The information stored in mobility management optimizationfunction 230 may be stored as a database in memory 430, for example. Asshown, mobility management optimization function 230 may include apredictive mobility determination logic 500, UE location database 502,traffic information database 505, cell site coverage database 510,handover schedule prediction engine 515, handover schedule database 520,and predictive handover execution logic 525.

Predictive mobility determination logic 500 includes logic configured toperiodically receive information from UE location database 502 thatidentifies a geographic location of UEs 215 and determine whether toapply predictive mobility management. For example, consistent withembodiments described herein, UEs 215 may be configured to periodically(e.g., every 1-2 seconds) provide location information, such as globalpositioning satellite (GPS) system location information to network 240.In other implementations, other location determining technology may beused to ascertain a geographic location of UEs 215, such as signaltriangulation, etc. The provided location information may be stored andregularly updated in UE location database 502. Predictive mobilitydetermination logic 500 may, based on the UE location information andtimestamp information associated therewith stored in database 502,ascertain a speed and direction of travel of UEs 215. Based on thelocation, speed, and direction of travel, predictive mobilitydetermination logic 500 may determine whether predictive mobilitymanagement is appropriate for handling cell site handovers. For example,based on the location, speed, and direction of travel, predictivemobility determination logic 500 may determine that UE is on ahigh-speed roadway, such as roadway 105, that may require multiple,frequent intra- and/or inter-cell site handovers. Regardless of theoutcome of this decision, predictive mobility determination logic 500may continually receive UE location information, so as to adjust thedecision process over time.

Traffic information database 505 may include information indicative oftraffic flow along support roadways. For example, traffic informationdatabase 505 may include average traffic flow rate information forsupported roadways. The information may be broken down by geographicsegments and day/time. The average traffic flow rate may be calculatedbased on both current and historical speed information for UE devices215 traveling on each roadway. For example, traffic information database505 may include roadway traffic information provided as a deviation fromaverage or from posted speed limits for each roadway. For example, aparticular stretch of roadway during rush hour may have an averagedeviation of −10 miles per hour over the posted speed limits, while thesame stretch of roadway during the mid-day has an average deviation of+10 miles per hour. In some implementations, the data on supportedroadways may be broken down based on cell site coverage or based onphysical distances. Furthermore, although the term “rush hour” was usedabove, in some implementations, the average speed may be calculatedindividually for any prescribed period of time, such as each minute,hour, etc.

Cell site coverage database 510 includes information identifyinggeographic coverage information for cell sites 225 as well as thecoverage zones for each relevant antenna beam associated with each cellsite 225. For example, cell site coverage database 510 may include, foreach cell site 225 and antenna beam, corresponding coverage zones for asupported roadway. As with the traffic information, coverage zoneinformation may be provided as relative roadway distances (e.g.,relative to a starting point of the roadway), or as absolute (e.g., GPS)geographically boundaries. As new cell sites 225 are brought online, orcapabilities change, the information in cell site coverage database 510may be updated to reflect such changes.

Handover schedule prediction engine 515 includes logic for generating ormodifying a predictive handover schedule for particular UEs 215. Forexample, handover schedule prediction engine 515 may be configured togenerate a predictive handover schedule based on the location and speedinformation for a particular UE 215, the traffic information stored intraffic information database 505, and the cell site coverage informationstored in cell site coverage database 510. For example, in someimplementations, handover schedule prediction engine 515 may beconfigured to schedule network-enforced handovers based on the speed ofUE 215, the predicted speed deviation at each handover location based onthe traffic information, the locations of the beam, and cell sitecoverage areas. The predictive handover schedule may be stored inhandover schedule database 520 for use in executing or implementing theidentified schedule.

By way of example, handover schedule prediction engine 515 retrieves,for each UE 215, instances of location and at various times (t),including predictive times. Such information may take the form:

UE_(i)={{t₀, {x₀,y₀}, {v_(x0), v_(y0)}}, {t₁, {x₁,y₁}, {v_(x1),v_(y1)}}, . . . , {t_(n), {x_(n),y_(n)}, {v_(xn), v_(yn)}},

where i denotes the individual UE (in a set of UEs), x and y denote thelocation of the UE and may correspond to, for example, latitude andlongitude values, v_(x) and v_(y) denote the speed in the x and ydirections, and the subscripts (0-n) denote that values at theparticular time instances. As described above, such times instancesinclude instances in the future, for which the handover schedule is tobe generated. The predicted future locations and speed values for eachUE may be adjusted based on information retrieved by traffic informationdatabase 505.

In addition to instances of UE location and speed, handover scheduleprediction engine 515 may also retrieve cell site coverage informationfrom cell site coverage database 510. For example, for each beam andcell site, coverage value may be expressed in terms of locations, or arange of locations.

Based on the actual and predicted UE location and speed information andthe cell site coverage location information, handover scheduleprediction engine 515 may output, for each UE, cell site and beaminformation for each time instance. In some examples, this output maytake the form:

UE_(i)={{t₀, C₀, B₀}, {t₀, C₁, B₁}, {t₂, C₂, B₂}, . . . , {t_(n), C_(n),B_(n)},

where C and B refer to the cell site and beam IDs for the respectivetimes.

Predictive handover execution logic 525 includes logic for signalingcell sites 225 to initiate intra- or inter-cell site handover processingbased on information included in the predictive handover schedule, asstored in handover schedule database 520. For example, for beamswitching intra-cell site handovers (e.g., time instances in thepredictive handover schedule in which the beam ID changes, but cell siteID does not), predictive handover execution logic 525 may transmitinstructions to a cell site to switch beams for UE 215 at the timedesignated in the predictive handover schedule. Similarly, forinter-cell site handovers (e.g., time instances in the predictivehandover schedule in which the cell site ID changes), predictivehandover execution logic 525 may transmit instructions to a cell site tohandover UE 215 to a designated target cell site at the time designatedin the predictive handover schedule.

FIG. 6 is a flow diagram of an exemplary process 600 for optimizingmobility management consistent with embodiments described herein. Theexemplary process of FIG. 6 may be implemented by mobility managementoptimization function 230, in conjunction with cell sites 225 andintervening network components.

The exemplary process includes mobility management optimization function230 periodically receiving or retrieving location information for a UE215 (block 605). For example, as described above, UE 215 mayperiodically provide location information, such as GPS locationinformation, to network 240 for use in providing network services. Basedon the received location information and time information associatedtherewith, mobility management optimization function 230 may calculatespeed and direction of travel information for UE 215, using, forexample, time and location data (block 610).

Using the location, speed, and direction of travel information, mobilitymanagement optimization function 230 may determine whether to applypredictive mobility management to UE 215 (block 615). For example,mobility management optimization function 230 may determine that thelocation, speed, and direction of travel information indicates that UE215 is on or is entering a high-speed roadway or other transportationvenue (e.g., railway, subway, etc.), which may cause frequent intra- andinter-cell handovers.

If mobility management optimization function 230 determines not to applypredictive mobility management (block 615—NO), process 600 returns toblock 605 for subsequent location information reception. However, whenmobility management optimization function 230 determines that predictivemobility management is to be applied (block 615—YES), mobilitymanagement optimization function 230 generates a predictive handoverschedule for UE 215 (block 620). For example, mobility managementoptimization function 230 may predict intra-(beam switching) andinter-cell site handover timings based on the location, speed, anddirection of travel information, as well as cell site coverageinformation for other cell sites 225 (e.g., cell sites proximate to thehigh-speed roadway) in network 240 for which predictive mobilitymanagement may be applied, such as cell sites 225 proximate to thehigh-speed roadway. As described above, cell site coverage informationmay be retrieved from cell site coverage database 510.

In some implementations, the predictive handover schedule may further bebased on current or historical traffic information associated with thepredicted path of UE 215. As described above, traffic informationdatabase 505 may store information indicative of speeds of UE devices atparticular times and locations. This information may be used by mobilitymanagement optimization function 230 to predict likely changes in speedof UE device 215 that may affect the schedule for predicted handovers.In still other implementations, historical travel information of UEdevice 215 may be used to generate the predicted handover schedule, orwhether to resume traditional handover processing. For example, assumethat UE device 215 regularly travels high-speed roadway between definedlocations (e.g., home and work) at particular times (or time ranges) anddays. Mobility management optimization function 230 may use informationregarding such historical travel patterns to predict likely destinationlocation for the predictive mobility management processing. In stillfurther embodiments, mobility management optimization function 230 maymodify or adapt the predictive handover schedule, based on dynamicchanges to traffic information, user device location or speed, or acombination thereof. Consistent with embodiments described herein, thepredictive handover schedule may identify the particular beam switchingand cell site handover timings for UE 215.

Next, mobility management optimization function 230 may initiate intra-and inter-cell site handovers at the times identified in the predictivehandover schedule (block 625). For example, mobility managementoptimization function 230 may signal a cell site 225 to switch beams forUE 215 at particular times based on the generated predictive handoverschedule. FIG. 7 is a signal diagram illustrating exemplary processingof such a schedule-based beam switching between a series of beamsfollowing initial RACH (random access channel) beam selection by UE(prior to initiation of predictive mobility management).

As shown in FIG. 7, a cell site 225-1 transmits UE-specific beaminformation (705) to UE 215-1 via the initially selected beam. Based onthe predictive handover schedule, mobility management optimizationfunction 230 transmits a beam switch message (710) to cell site 225-1identifying a next beam to which the UE 215-1 is to use. UE 215-1 andcell site 225-1 then perform signal synchronization (715) to affect thehandover of UE 215-1 to the identified beam. For example, UE 215-1 andcell site 225-1 may exchange primary and secondary synchronizationsignals, a primary broadcast channel (PBCH) signal, etc.

At a next time instance that includes a beam change as identified in thepredictive handover schedule, mobility management optimization function230 transmits another beam switch message (720) to cell site 225-1identifying a next beam to which the UE 215-1 is to use. UE 215-1 andcell site 225-1 then perform signal synchronization (725) to affect thehandover of UE 215-1 to the identified beam. This process continuesuntil the predictive handover schedule indicates that no additionalbeams are scheduled on cell site 225-1, as indicated, for example, by acell site ID change instance in the predictive handover schedule. Incontrast to traditional beam switching processing, the above-describedprocess does not require beam measurement information to be shared ornegotiated between UE 215-1 and cell site 225-1 prior to beam switching.Rather, the identity of the new beam is provided to cell site 225-1 bymobility management optimization function 230.

Returning to FIG. 6, in addition to intra-cell site handovers (beamswitching), the predictive handover schedule may also indicate the timesand particular inter-cell site handovers for UE 215-1, e.g., instancesin the predictive handover schedule that indicate a cell site ID change.FIG. 8 is a signal diagram illustrating exemplary processing of such aschedule-based inter-cell site handover consistent with embodimentsdescribed herein. As shown in FIG. 8, mobility management optimizationfunction 230 transmits a handover message (800) to source cell site225-1. For example, handover message 800 may identify target cell site225-2 toward which UE 215-1 is moving. In response, source cell site225-1 transmits a reconfiguration message (805), to UE 215-1 thatidentifies the target cell site 225-2. UE 215-1 then performs randomaccess (810) and radio resource control (RRC) configuration (815) withtarget cell site 225-2 to affect the handover to target cell site 225-2.Target cell site 225-2 in response to the handover, transmits a pathswitch request (820) to control plane function 890, which transmits amodify bearer request (825) to user plane function 895. User planefunction 890 and control plane function 895 transmit appropriateresponses (830/835).

At a next time instance that includes a cell site change as identifiedin the predictive handover schedule, mobility management optimizationfunction 230 transmits another handover message (840) to cell site225-2. For example, handover message 840 may identify a next cell site225-3 toward which UE 215-1 is moving. In response, cell site 225-2transmits a reconfiguration message (845), to UE 215-1 that identifiesthe target cell site 225-3. UE 215-1 then performs random access (850)and radio resource control (RRC) configuration (855) with target cellsite 225-3 to effect the handover to target cell site 225-3. Althoughnot depicted in FIG. 8, cell site 225-3 in response to the handover mayperform additional processing as described above to effect a handoverfrom cell site 225-2 to cell site 225-3. This process may continue untilthe predictive handover schedule indicates that no additional cell sites225 are included in the predictive scheduled on cell site 225-1. Incontrast to traditional inter-cell site handover processing, theabove-described process does not require measurement information, suchas beam reference signal (BRS) measurement information for each of asource cell site and a target cell site. Rather, the identity of alltarget cell sites are provided and directed by mobility managementoptimization function 230.

The foregoing description of implementations provides illustration anddescription but is not intended to be exhaustive or to limit theinvention to the precise form disclosed. Modifications and variationsare possible in light of the above teachings or may be acquired frompractice of the invention. For example, while series of blocks andsignal messages have been described with respect to FIGS. 6, 7, and 8,the order of the blocks and signal messages may be varied in otherimplementations. Moreover, non-dependent blocks may be performed inparallel.

Certain features described above may be implemented as “logic” or a“unit” that performs one or more functions. This logic or unit mayinclude hardware, such as one or more processors, microprocessors,application specific integrated circuits, or field programmable gatearrays, software, or a combination of hardware and software.

No element, act, or instruction used in the description of the presentapplication should be construed as critical or essential to theinvention unless explicitly described as such. Also, as used herein, thearticle “a” is intended to include one or more items. Further, thephrase “based on” is intended to mean “based, at least in part, on”unless explicitly stated otherwise.

To the extent the aforementioned embodiments collect, store, or employpersonal information of individuals, it should be understood that suchinformation shall be collected, stored, and used in accordance with allapplicable laws concerning protection of personal information.Additionally, the collection, storage, and use of such information canbe subject to consent of the individual to such activity, for example,through well known “opt-in” or “opt-out” processes as can be appropriatefor the situation and type of information. Storage and use of personalinformation can be in an appropriately secure manner reflective of thetype of information, for example, through various encryption andanonymization techniques for particularly sensitive information.

In the preceding specification, various preferred embodiments have beendescribed with reference to the accompanying drawings. It will, however,be evident that various modifications and changes may be made thereto,and additional embodiments may be implemented, without departing fromthe broader scope of the invention as set forth in the claims thatfollow. The specification and drawings are accordingly to be regarded inan illustrative rather than restrictive sense.

What is claimed is:
 1. A method, comprising: receiving, by a networkfunction executing on a service provider network, geographic locationinformation associated with a user equipment device (UE), wherein the UEis associated with a vehicle; generating, by the network function, apredictive handover schedule based on the received location information;and initiating, by the network function, handover processing based onthe predictive handover schedule, wherein initiating the handoverprocessing comprises: transmitting, at times based on the predictivehandover schedule, a handover initiation message to each of a pluralityof cell sites in the service provider wireless network, wherein, uponreceipt of a respective handover initiation message, each cell siteinitiates handover processing based on the received handover initiationmessage.
 2. The method of claim 1, wherein receiving the geographiclocation information comprises periodically receiving global positioningsystem (GPS) location information associated with the UE.
 3. The methodof claim 1, further comprises: calculating a speed and direction oftravel of the UE based on the received geographic location information;and determining whether to apply predictive mobility management based onthe location information, speed, and direction of travel.
 4. The methodof claim 3, wherein generating the predictive handover schedule furthercomprises: generating the predictive handover schedule based on thelocation information, speed, direction of travel information, cell sitecoverage information, and traffic information.
 5. The method of claim 4,wherein the cell site coverage information comprises identification,geographic coverage, and capabilities information for the plurality ofcell sites.
 6. The method of claim 5, wherein each of the plurality ofcell sites comprises a next generation node B (gNB) capable of operatingin the millimeter wave (mmWave) spectrum and wherein the serviceprovider wireless network comprises a fifth generation (5G) public landmobile network (PLMN).
 7. The method of claim 6, wherein the cell sitecoverage information further comprises antenna beam coverage informationfor each respective antenna beam associated with a particular cell sitein the plurality of cell sites.
 8. The method of claim 7, wherein thepredictive handover schedule identifies predicted timings for inter-cellsite handovers and beam switching handovers.
 9. The method of claim 8,wherein transmitting the one or more handover initiation messages, forbeam switching handovers, comprises transmitting a beam switch messageto a cell site, wherein the beam switch messages identifies a beam towhich the UE is to switch to.
 10. The method of claim 8, whereintransmitting the one or more handover initiation messages, forinter-cell site handovers, comprises transmitting a target cell siteidentification message to a cell site currently serving the UE.
 11. Anetwork function executing on a service provider network, comprising: acommunication interface configured to: receive geographic locationinformation associated with a user equipment device (UE), wherein the UEis associated with a vehicle; and a processing unit configured to:generate a predictive handover schedule based on the received locationinformation; and initiate handover processing based on the predictivehandover schedule, wherein the processing unit configured to initiatethe handover processing is further configured to: transmit, at timesbased on the predictive handover schedule, a handover initiation messageto each of a plurality of cell sites in the service provider wirelessnetwork, wherein, upon receipt of a respective handover initiationmessage, each cell site initiates handover processing based on thereceived handover initiation message.
 12. The network function of claim11, wherein the communication interface is further configured toperiodically receive global positioning system (GPS) locationinformation associated with the UE.
 13. The network function of claim11, wherein the processing unit is further configured to: calculate aspeed and direction of travel of the UE based on the received geographiclocation information; and determine whether to apply predictive mobilitymanagement based on the location information, speed, and direction oftravel.
 14. The network function of claim 13, wherein the processingunit configured to generate the predictive handover schedule is furtherconfigured to: generate the predictive handover schedule based on thelocation information, speed, and direction of travel, cell site coverageinformation, and traffic information.
 15. The network function of claim14, wherein the cell site coverage information comprises identification,geographic coverage, and capabilities information for the plurality ofcell sites.
 16. The network function of claim 15, wherein the cell sitecoverage information further comprises antenna beam coverage informationfor each respective antenna beam associated with a particular cell sitein the plurality of cell sites.
 17. A non-transitory storage mediumstoring instructions executable by a network function executing on aservice provider network, wherein the instructions comprise instructionsto cause the network function to: receive geographic locationinformation associated with a user equipment device (UE), wherein the UEis associated with a vehicle; generate a predictive handover schedulebased on the received location information; and initiate handoverprocessing based on the predictive handover schedule, wherein theinstructions to cause the network device to initiate the handoverprocessing further cause the network device to: transmit, at times basedon the predictive handover schedule, a handover initiation message toeach of a plurality of cell sites in the service provider wirelessnetwork, wherein, upon receipt of a respective handover initiationmessage, each cell site initiates handover processing based on thereceived handover initiation message.
 18. The non-transitory storagemedium of claim 17, wherein the instruction further compriseinstructions to cause the network device to: calculate a speed anddirection of travel of the UE based on the received geographic locationinformation; and determine whether to apply predictive mobilitymanagement based on the location information, speed, and direction oftravel.
 19. The non-transitory storage medium of claim 18, wherein theinstructions to cause the network device to generate the predictivehandover schedule further comprises instructions to: generate thepredictive handover schedule based on the location information, speed,and direction of travel, cell site coverage information, and trafficinformation.
 20. The non-transitory storage medium of claim 19, whereinthe cell site coverage information comprises identification, geographiccoverage, and capabilities information for the plurality of cell sites,wherein each of the plurality of cell sites comprises a next generationnode B (gNB) capable of operating in the millimeter wave (mmWave)spectrum and wherein the service provider wireless network comprises afifth generation (5G) public land mobile network (PLMN), and wherein thecell site coverage information further comprises antenna beam coverageinformation for each respective antenna beam associated with aparticular cell site in the plurality of cell sites.